{"id":8655,"date":"2026-02-03T13:31:25","date_gmt":"2026-02-03T12:31:25","guid":{"rendered":"https:\/\/nersc.no\/?p=8655"},"modified":"2026-02-03T13:31:37","modified_gmt":"2026-02-03T12:31:37","slug":"more-accurate-arctic-sea-ice-predictions-with-satellite-data","status":"publish","type":"post","link":"https:\/\/nersc.no\/en\/features\/more-accurate-arctic-sea-ice-predictions-with-satellite-data\/","title":{"rendered":"More accurate Arctic sea-ice predictions with satellite data"},"content":{"rendered":"

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More accurate Arctic sea-ice predictions with satellite data<\/h1><\/div>[vc_column_text css=””]Researchers at the Nansen Center have improved seasonal Arctic sea-ice predictions by adding satellite-based sea-ice thickness data to a global climate model. This information helps predict melting and break ups, and thus sea-ice conditions more accurately. Such improvements are crucial for understanding a rapidly changing Arctic.<\/strong><\/p>\n

The Arctic is warming faster than any other region on Earth. Rising temperatures in the ocean and atmosphere are causing sea ice to thin and retreat at an alarming pace. These changes ripple through ecosystems, affect Arctic wildlife, and challenge local communities. They also influence tourism, shipping routes, and resource extraction. Reliable seasonal predictions of sea-ice conditions, such as its extent, thickness, and the position of the ice edge, are increasingly important. They help scientists, policymakers, and industries prepare for what lies ahead in a region undergoing dramatic transformation.<\/p>\n

What is new in this study?<\/strong><\/p>\n

Our researchers have taken a major step forward by integrating sea-ice thickness data from two different satellite products into the Norwegian Climate Prediction Model, NorCPM: CS2SMOS and ENVISAT (se info box). By assimilating these datasets, the work has extended the timeframe for assessments to 21 years and strengthened the foundation for predicting Arctic sea-ice conditions.<\/p>\n

What are the outcomes?<\/strong><\/p>\n

The introduction of observation data on ice thickness into the climate model has proven to be very important. The study clearly shows that forecasts for both sea-ice extent and thickness become more accurate when this data is included. It makes a particular difference to forecasts of the ice edge, which is important for navigation, environmental monitoring, and ecosystem analysis.<\/p>\n

\u201cIncluding observations of ice thickness has made our models more accurate when it comes to forecasting ice thickness. But the improvement on the sea-ice edge is much less than previously assumed and is only noticeable for September. It remains to be further investigated whether this limitation is intrinsic to our models or whether other sources of uncertainty are more predominant,\u201d says Fran\u00e7ois Counillon, research director at the Nansen Center and co-author of the publication.<\/p>\n

Impact beyond science<\/strong><\/p>\n

Seasonal sea\u2011ice predictions matter far beyond the research communities. Companies in shipping, energy, food production, insurance, consulting, and risk management rely on such information for planning their activities in polar regions. Government agencies use forecasts to support policy development, climate adaptation, and Arctic governance. They are also valuable for organisations involved in logistics and resource management in the North. Improved predictions support wildlife and habitat protection, safer navigation and tourism, and better resource management for local communities adapting to rapid change.<\/p>\n

In short: better data leads to better decisions in a changing Arctic.<\/p>\n

Key researchers:<\/strong> Fran\u00e7ois Counillon<\/span><\/a>, Yiguo Wang<\/span><\/a>[\/vc_column_text][\/vc_column][vc_column width=”1\/3″ css=”.vc_custom_1695033709348{padding-right: 0px !important;}”]

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Publication<\/strong><\/h3>\n

\u00abEnhancing sea ice knowledge through assimilation of sea ice thickness from ENVISAT and CS2SMOS\u00bb, in The Cryosphere<\/em><\/p>\n

Read the publication here<\/span><\/a>.<\/p>\n

The publication has been produced by postdoc Nicholas Williams, with the help of Fran\u00e7ois Counillon and Yiguo Wang. Williams has since moved to a new position at Sun-Yat-Sen University in China.<\/p><\/div>

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Sea-ice thickness: Why it counts<\/strong><\/h3>\n

Sea-ice thickness determines how resilient sea ice is to melting and breaking. It is a key factor for predicting future sea-ice conditions.<\/p><\/div>

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What is NorCPM?<\/strong><\/h3>\n

The Norwegian Climate Prediction Model NorCPM<\/span><\/a> combines observations and simulations to forecast climate conditions months to years ahead. The Nansen Center is taking part in its ongoing development and improvement.<\/p><\/div>

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Which satellite products were used?<\/strong><\/h3>\n

CS2SMOS, a widely used product, combines data from the CryoSat-2 and SMOS satellites and covers the period from 2010 onwards.<\/p>\n

ENVISAT, an older dataset, spans 2002\u20132012 and has never before been used in this way. Despite some limitations, it adds provides valuable information about the historical development of the sea-ice thickness.<\/p><\/div>[\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"

[vc_row][vc_column][\/vc_column][\/vc_row][vc_row][vc_column width=”2\/3″ css=”.vc_custom_1693479579188{background-color: #ffffff !important;}”][vc_column_text css=””]Researchers at the Nansen Center have improved seasonal Arctic sea-ice predictions by adding satellite-based sea-ice thickness data to a global climate model. This information helps predict melting and break ups, and thus sea-ice conditions more accurately. Such improvements are crucial for understanding a rapidly changing Arctic. The Arctic is warming […]<\/p>\n","protected":false},"author":4,"featured_media":8657,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","footnotes":""},"categories":[80],"tags":[],"class_list":["post-8655","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-features"],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-04-26 10:10:52","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/posts\/8655","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/comments?post=8655"}],"version-history":[{"count":2,"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/posts\/8655\/revisions"}],"predecessor-version":[{"id":8661,"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/posts\/8655\/revisions\/8661"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/media\/8657"}],"wp:attachment":[{"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/media?parent=8655"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/categories?post=8655"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/nersc.no\/en\/wp-json\/wp\/v2\/tags?post=8655"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}